Source-linked AI cost planning

Model the full cost of an AI agent.

Estimate monthly spend, cost per request and cost per successful task—from token usage and caching to retries, tools, RAG and observability.

● Source-linked rate records▧ Transparent assumptions◌ No account required

Agent cost calculator

See the assumption behind every number.

Workload
Tasks completed without needing a rerun
Model usage
Source-linked public list pricing; update before planning spend
Agent behavior
Extra requests after failures or incomplete outputs
Traces, logs, evaluation and retention allowance
Optional escalation or quality-review allowance
Visible uncertainty around your chosen assumptions
RAG & tools
Third-party APIs, browser or search services
Embeddings, vector reads and storage allowance

Estimated monthly cost

$0

Planning range: —

↘ Model your drivers
$0.000Cost / request
$0.000Cost / successful task
—Cost / 100 users

Cost breakdown (monthly)

Model tokens$0
Tools & RAG$0
Observability$0
Human review$0
Retries$0
Top driver: model tokens

Try caching stable context to reduce repeated input cost.

⌁ How the estimate works

Monthly cost combines model tokens, tools, RAG, observability, human review and retry behavior from your editable assumptions.

monthly = model + tools + RAG + observability + human review + retries

▣ Sources & assumptions

Rate records are source-linked and versioned. Always check the provider page before final budgeting.

? FAQ

Why can an invoice differ? Contracts, taxes, regional pricing, tool metering and usage behavior can change the final bill.

Why teams use it

Token price is only the beginning.

▦ Plan per outcome

Translate model usage into cost per successful task, not only a monthly token total.

⌘ Include agent behavior

Retries, multi-step execution, retrieval and tools can shift the economics more than a model switch.

◌ Keep assumptions visible

Every estimate has an editable input, dated rate record or clear boundary. No hidden multipliers.